Bibliographic record
Abstract
Philosophy \nThrough my art work, I seek to reawaken man to the \npower of nature and his relationship to it, because, \nthrough my actions as an artist, I become more and more \naware of this interconnection. The force of nature as \nit sculpts its contours has long held my attention. In \nextensive travel throughout the United States, Canada, \nMexico, Europe and Japan, my eyes have constantly sought \nout the characteristics of landform. Form created by \nerosion of water, wind and snow have kindled in me intense \njoy of recognition of my source as a segment of \nthis universal process. I am made aware that the forces \nof life act through and on me as they do on the mountain. \nRealization of this connection to natural processes has \ngiven me courage to allow my life to develop according \nto the plan and influences I cannot control. Letting go \ncontrol allows the forces of life within and around me \nto contour my existence with the beauty that has been \ndistorted by my fear of allowing the natural forces entry \nand action, the beauty choked off by my own insistence on \nself-control and the power of reason. Through my art, I \nam awakening myself. This is a process I want to share. (See more in text)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.086 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".